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Add default definition for GetColWiseData and GetColWiseData (#5413)
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* add default definition for GetColWiseData and GetColWiseData

* fix warnings of template instantiation

* remove files in Makevars and LightGBM.vcxproj
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@shiyu1994
shiyu1994 authored Aug 16, 2022
1 parent 4a9b08e commit 9489f87
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Showing 9 changed files with 364 additions and 435 deletions.
4 changes: 0 additions & 4 deletions R-package/src/Makevars.in
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Original file line number Diff line number Diff line change
Expand Up @@ -37,10 +37,6 @@ OBJECTS = \
io/parser.o \
io/train_share_states.o \
io/tree.o \
io/dense_bin.o \
io/sparse_bin.o \
io/multi_val_dense_bin.o \
io/multi_val_sparse_bin.o \
metric/dcg_calculator.o \
metric/metric.o \
objective/objective_function.o \
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4 changes: 0 additions & 4 deletions R-package/src/Makevars.win.in
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Original file line number Diff line number Diff line change
Expand Up @@ -38,10 +38,6 @@ OBJECTS = \
io/parser.o \
io/train_share_states.o \
io/tree.o \
io/dense_bin.o \
io/sparse_bin.o \
io/multi_val_dense_bin.o \
io/multi_val_sparse_bin.o \
metric/dcg_calculator.o \
metric/metric.o \
objective/objective_function.o \
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364 changes: 364 additions & 0 deletions src/io/bin.cpp
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Expand Up @@ -719,4 +719,368 @@ namespace LightGBM {
}
}

template <>
const void* DenseBin<uint8_t, false>::GetColWiseData(
uint8_t* bit_type,
bool* is_sparse,
std::vector<BinIterator*>* bin_iterator,
const int /*num_threads*/) const {
*is_sparse = false;
*bit_type = 8;
bin_iterator->clear();
return reinterpret_cast<const void*>(data_.data());
}

template <>
const void* DenseBin<uint16_t, false>::GetColWiseData(
uint8_t* bit_type,
bool* is_sparse,
std::vector<BinIterator*>* bin_iterator,
const int /*num_threads*/) const {
*is_sparse = false;
*bit_type = 16;
bin_iterator->clear();
return reinterpret_cast<const void*>(data_.data());
}

template <>
const void* DenseBin<uint32_t, false>::GetColWiseData(
uint8_t* bit_type,
bool* is_sparse,
std::vector<BinIterator*>* bin_iterator,
const int /*num_threads*/) const {
*is_sparse = false;
*bit_type = 32;
bin_iterator->clear();
return reinterpret_cast<const void*>(data_.data());
}

template <>
const void* DenseBin<uint8_t, true>::GetColWiseData(
uint8_t* bit_type,
bool* is_sparse,
std::vector<BinIterator*>* bin_iterator,
const int /*num_threads*/) const {
*is_sparse = false;
*bit_type = 4;
bin_iterator->clear();
return reinterpret_cast<const void*>(data_.data());
}

template <>
const void* DenseBin<uint8_t, false>::GetColWiseData(
uint8_t* bit_type,
bool* is_sparse,
BinIterator** bin_iterator) const {
*is_sparse = false;
*bit_type = 8;
*bin_iterator = nullptr;
return reinterpret_cast<const void*>(data_.data());
}

template <>
const void* DenseBin<uint16_t, false>::GetColWiseData(
uint8_t* bit_type,
bool* is_sparse,
BinIterator** bin_iterator) const {
*is_sparse = false;
*bit_type = 16;
*bin_iterator = nullptr;
return reinterpret_cast<const void*>(data_.data());
}

template <>
const void* DenseBin<uint32_t, false>::GetColWiseData(
uint8_t* bit_type,
bool* is_sparse,
BinIterator** bin_iterator) const {
*is_sparse = false;
*bit_type = 32;
*bin_iterator = nullptr;
return reinterpret_cast<const void*>(data_.data());
}

template <>
const void* DenseBin<uint8_t, true>::GetColWiseData(
uint8_t* bit_type,
bool* is_sparse,
BinIterator** bin_iterator) const {
*is_sparse = false;
*bit_type = 4;
*bin_iterator = nullptr;
return reinterpret_cast<const void*>(data_.data());
}

template <>
const void* SparseBin<uint8_t>::GetColWiseData(
uint8_t* bit_type,
bool* is_sparse,
std::vector<BinIterator*>* bin_iterator,
const int num_threads) const {
*is_sparse = true;
*bit_type = 8;
for (int thread_index = 0; thread_index < num_threads; ++thread_index) {
bin_iterator->emplace_back(new SparseBinIterator<uint8_t>(this, 0));
}
return nullptr;
}

template <>
const void* SparseBin<uint16_t>::GetColWiseData(
uint8_t* bit_type,
bool* is_sparse,
std::vector<BinIterator*>* bin_iterator,
const int num_threads) const {
*is_sparse = true;
*bit_type = 16;
for (int thread_index = 0; thread_index < num_threads; ++thread_index) {
bin_iterator->emplace_back(new SparseBinIterator<uint16_t>(this, 0));
}
return nullptr;
}

template <>
const void* SparseBin<uint32_t>::GetColWiseData(
uint8_t* bit_type,
bool* is_sparse,
std::vector<BinIterator*>* bin_iterator,
const int num_threads) const {
*is_sparse = true;
*bit_type = 32;
for (int thread_index = 0; thread_index < num_threads; ++thread_index) {
bin_iterator->emplace_back(new SparseBinIterator<uint32_t>(this, 0));
}
return nullptr;
}

template <>
const void* SparseBin<uint8_t>::GetColWiseData(
uint8_t* bit_type,
bool* is_sparse,
BinIterator** bin_iterator) const {
*is_sparse = true;
*bit_type = 8;
*bin_iterator = new SparseBinIterator<uint8_t>(this, 0);
return nullptr;
}

template <>
const void* SparseBin<uint16_t>::GetColWiseData(
uint8_t* bit_type,
bool* is_sparse,
BinIterator** bin_iterator) const {
*is_sparse = true;
*bit_type = 16;
*bin_iterator = new SparseBinIterator<uint16_t>(this, 0);
return nullptr;
}

template <>
const void* SparseBin<uint32_t>::GetColWiseData(
uint8_t* bit_type,
bool* is_sparse,
BinIterator** bin_iterator) const {
*is_sparse = true;
*bit_type = 32;
*bin_iterator = new SparseBinIterator<uint32_t>(this, 0);
return nullptr;
}

#ifdef USE_CUDA_EXP
template <>
const void* MultiValDenseBin<uint8_t>::GetRowWiseData(uint8_t* bit_type,
size_t* total_size,
bool* is_sparse,
const void** out_data_ptr,
uint8_t* data_ptr_bit_type) const {
const uint8_t* to_return = data_.data();
*bit_type = 8;
*total_size = static_cast<size_t>(num_data_) * static_cast<size_t>(num_feature_);
CHECK_EQ(*total_size, data_.size());
*is_sparse = false;
*out_data_ptr = nullptr;
*data_ptr_bit_type = 0;
return to_return;
}

template <>
const void* MultiValDenseBin<uint16_t>::GetRowWiseData(uint8_t* bit_type,
size_t* total_size,
bool* is_sparse,
const void** out_data_ptr,
uint8_t* data_ptr_bit_type) const {
const uint16_t* data_ptr = data_.data();
const uint8_t* to_return = reinterpret_cast<const uint8_t*>(data_ptr);
*bit_type = 16;
*total_size = static_cast<size_t>(num_data_) * static_cast<size_t>(num_feature_);
CHECK_EQ(*total_size, data_.size());
*is_sparse = false;
*out_data_ptr = nullptr;
*data_ptr_bit_type = 0;
return to_return;
}

template <>
const void* MultiValDenseBin<uint32_t>::GetRowWiseData(uint8_t* bit_type,
size_t* total_size,
bool* is_sparse,
const void** out_data_ptr,
uint8_t* data_ptr_bit_type) const {
const uint32_t* data_ptr = data_.data();
const uint8_t* to_return = reinterpret_cast<const uint8_t*>(data_ptr);
*bit_type = 32;
*total_size = static_cast<size_t>(num_data_) * static_cast<size_t>(num_feature_);
CHECK_EQ(*total_size, data_.size());
*is_sparse = false;
*out_data_ptr = nullptr;
*data_ptr_bit_type = 0;
return to_return;
}

template <>
const void* MultiValSparseBin<uint16_t, uint8_t>::GetRowWiseData(
uint8_t* bit_type,
size_t* total_size,
bool* is_sparse,
const void** out_data_ptr,
uint8_t* data_ptr_bit_type) const {
const uint8_t* to_return = data_.data();
*bit_type = 8;
*total_size = data_.size();
*is_sparse = true;
*out_data_ptr = reinterpret_cast<const uint8_t*>(row_ptr_.data());
*data_ptr_bit_type = 16;
return to_return;
}

template <>
const void* MultiValSparseBin<uint16_t, uint16_t>::GetRowWiseData(
uint8_t* bit_type,
size_t* total_size,
bool* is_sparse,
const void** out_data_ptr,
uint8_t* data_ptr_bit_type) const {
const uint8_t* to_return = reinterpret_cast<const uint8_t*>(data_.data());
*bit_type = 16;
*total_size = data_.size();
*is_sparse = true;
*out_data_ptr = reinterpret_cast<const uint8_t*>(row_ptr_.data());
*data_ptr_bit_type = 16;
return to_return;
}

template <>
const void* MultiValSparseBin<uint16_t, uint32_t>::GetRowWiseData(
uint8_t* bit_type,
size_t* total_size,
bool* is_sparse,
const void** out_data_ptr,
uint8_t* data_ptr_bit_type) const {
const uint8_t* to_return = reinterpret_cast<const uint8_t*>(data_.data());
*bit_type = 32;
*total_size = data_.size();
*is_sparse = true;
*out_data_ptr = reinterpret_cast<const uint8_t*>(row_ptr_.data());
*data_ptr_bit_type = 16;
return to_return;
}

template <>
const void* MultiValSparseBin<uint32_t, uint8_t>::GetRowWiseData(
uint8_t* bit_type,
size_t* total_size,
bool* is_sparse,
const void** out_data_ptr,
uint8_t* data_ptr_bit_type) const {
const uint8_t* to_return = data_.data();
*bit_type = 8;
*total_size = data_.size();
*is_sparse = true;
*out_data_ptr = reinterpret_cast<const uint8_t*>(row_ptr_.data());
*data_ptr_bit_type = 32;
return to_return;
}

template <>
const void* MultiValSparseBin<uint32_t, uint16_t>::GetRowWiseData(
uint8_t* bit_type,
size_t* total_size,
bool* is_sparse,
const void** out_data_ptr,
uint8_t* data_ptr_bit_type) const {
const uint8_t* to_return = reinterpret_cast<const uint8_t*>(data_.data());
*bit_type = 16;
*total_size = data_.size();
*is_sparse = true;
*out_data_ptr = reinterpret_cast<const uint8_t*>(row_ptr_.data());
*data_ptr_bit_type = 32;
return to_return;
}

template <>
const void* MultiValSparseBin<uint32_t, uint32_t>::GetRowWiseData(
uint8_t* bit_type,
size_t* total_size,
bool* is_sparse,
const void** out_data_ptr,
uint8_t* data_ptr_bit_type) const {
const uint8_t* to_return = reinterpret_cast<const uint8_t*>(data_.data());
*bit_type = 32;
*total_size = data_.size();
*is_sparse = true;
*out_data_ptr = reinterpret_cast<const uint8_t*>(row_ptr_.data());
*data_ptr_bit_type = 32;
return to_return;
}

template <>
const void* MultiValSparseBin<uint64_t, uint8_t>::GetRowWiseData(
uint8_t* bit_type,
size_t* total_size,
bool* is_sparse,
const void** out_data_ptr,
uint8_t* data_ptr_bit_type) const {
const uint8_t* to_return = data_.data();
*bit_type = 8;
*total_size = data_.size();
*is_sparse = true;
*out_data_ptr = reinterpret_cast<const uint8_t*>(row_ptr_.data());
*data_ptr_bit_type = 64;
return to_return;
}

template <>
const void* MultiValSparseBin<uint64_t, uint16_t>::GetRowWiseData(
uint8_t* bit_type,
size_t* total_size,
bool* is_sparse,
const void** out_data_ptr,
uint8_t* data_ptr_bit_type) const {
const uint8_t* to_return = reinterpret_cast<const uint8_t*>(data_.data());
*bit_type = 16;
*total_size = data_.size();
*is_sparse = true;
*out_data_ptr = reinterpret_cast<const uint8_t*>(row_ptr_.data());
*data_ptr_bit_type = 64;
return to_return;
}

template <>
const void* MultiValSparseBin<uint64_t, uint32_t>::GetRowWiseData(
uint8_t* bit_type,
size_t* total_size,
bool* is_sparse,
const void** out_data_ptr,
uint8_t* data_ptr_bit_type) const {
const uint8_t* to_return = reinterpret_cast<const uint8_t*>(data_.data());
*bit_type = 32;
*total_size = data_.size();
*is_sparse = true;
*out_data_ptr = reinterpret_cast<const uint8_t*>(row_ptr_.data());
*data_ptr_bit_type = 64;
return to_return;
}

#endif // USE_CUDA_EXP

} // namespace LightGBM
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